Sustainable Decision-Making Enhancement: Trust and Linguistic-Enhanced Conflict Measurement in Evidence Theory

Abstract

This research presents an advanced methodology to enhance conflict measurement within the Dempster–Shafer framework, integrating linguistic preferences and trust relationships for improved sustainability decision-making. By developing a unique algorithm, we introduce a novel approach to quantify inter-expert similarity and establish consensus thresholds. Furthermore, our study innovates with a dual-path adjustment mechanism to effectively reconcile discrepancies in expert opinions. These methodological advancements enable a more accurate and nuanced representation of expert judgments, facilitating superior decision support in sustainability-oriented applications. Through rigorous numerical simulations and a detailed case study, we validate our approach’s efficacy in optimizing decision-making processes, underscoring its potential to significantly influence sustainable practices and policy formulation. Our contributions not only advance theoretical understanding but also offer practical tools for incorporating expert insights into the pursuit of sustainability goals, marking a significant leap forward in decision-making research.